Content discovery based on speech input is at a similar stage of evolution compared to text-based input interfaces almost a decade ago. A user expresses intent using a fully formed spoken sentence, and then waits for a response. The response may then trigger the user to follow up with another full sentence. Analogous to this usage model, almost a decade ago the user expressed his or her entire intent in the form of fully formed keywords, and then submitted the fully entered search query. Text-based incremental search changed this operational paradigm. Text-based incremental search is described further in U.S. Pat. No. 7,895,218, entitled “Method and system for performing searches for television content using reduced text input” and filed May 24, 2005, the entire contents of which are incorporated by reference herein. In text-based incremental search, search results appear as the user types keywords (or even mere prefixes corresponding to keywords). Users now take for granted the ease of use of a text-based incremental search interface.
Speech-based content discovery systems are becoming reliable and useful enough to be incorporated into users' daily lives. While users have been conditioned by the ease of use of text-based incremental search, speech-based content discovery is also ushering in a slow change in intent expression. For example, speech-based content discovery provides an ability to speak users' minds directly, as opposed to translating thought into a string of keywords. While natural-language-based speech interfaces are primarily in the mobile and television environment, the desktop environment is also seeing the emergence of natural language interfaces, such as Facebook Graph search, where user types in a natural language query.